x-filter

# X Filter Score and filter collected materials for X content creation. Topics scoring ≥7 points enter the creation pool. ## Scoring System (满分10分) | Criteria | Weight | Description | |----------|--------|-------------| | **热度/趋势** | 4分 | Current popularity and trend momentum | | **争议性** | 2分 | Discussion potential and debate value | | **高价值** | 3分 | Information density and actionable insights | | **账号定位相关** | 1分 | Alignment with account positioning | **Threshold**: ≥7分 enters creation pool ## Prerequisites - Materials from x-collect (or manual input) - User profile from x-create/references/user-profile.md (for relevance scoring) ## Optional State (Feedback Loop) If available, use persisted state to improve filtering: - State dir: `~/.claude/skills/x-create/state/` - Negative samples: `rejected_topics.json` (SimilarityFilter) - Events log: `events.jsonl` (optional analytics) If state files don't exist, proceed normally. ## Workflow ### Input Accept materials from: 1. **x-collect output** - Structured material report 2. **Manual list** - User-provided topics/URLs 3. **Raw text** - Unstructured content to evaluate ### Scoring Process For each material/topic, score multiple dimensions and combine with weights. **Weighted score (recommended):** `FinalScore = Σ(w_i × s_i) - NegPenalty` Where: - `s_i` are per-dimension scores (0..max) - `w_i` come from `references/user-profile.md` (fallback to defaults) - `NegPenalty` is derived from similarity to rejected topics and other negative signals **1. 热度/趋势 (Trending Score: 0-4)** ``` 4分: 当前热门话题，大量讨论 3分: 近期热点，关注度上升 2分: 稳定话题，持续有人讨论 1分: 小众话题，关注度有限 0分: 过时话题，几乎无人讨论 ``` **(Optional) 新鲜度 (Freshness)** - If you can infer recency from sources, either: - fold it into Trending score, or - add a small bonus/penalty (e.g., +0.5 for <72h, -0.5 for >30d) **2. 争议性 (Controversy Score: 0-2)** ``` 2分: 明显争议，多方观点对立 1分: 存在不同看法，可引发讨论 0分: 共识性话题，难以引发讨论 ``` **3. 高价值 (Value Score: 0-3)** ``` 3分: 硬核干货，可直接指导行动 2分: 有价值信息，提供新视角 1分: 一般信息，了解即可 0分: 低价值，无实质内容 ``` **4. 账号定位相关 (Relevance Score: 0-1)** ``` 1分: 与账号定位高度相关 0分: 与账号定位关联较弱 ``` Check user profile at: `~/.claude/skills/x-create/references/user-profile.md` If not found, assume domains: [AI/科技, 创业, 个人成长] **SimilarityFilter (Negative Samples):** - If `~/.claude/skills/x-create/state/rejected_topics.json` exists, compare each candidate topic to rejected items. - If max similarity ≥ 0.85: mark as likely duplicate/low-value → strong penalty or direct reject. - If 0.75 ≤ similarity < 0.85: apply soft penalty (e.g., -2 points) and explain why. (Implementation via script): - `python ~/.claude/skills/x-create/scripts/x_state.py similarity --against rejected --text "{topic}" --topk 3` ### Output Format ```markdown # 选题筛选报告 ## 筛选时间 {timestamp} ## 用户定位 - 领域: {domains} - 人设: {persona_style} ## 筛选结果 ### Tier A：入选创作池 (≥7分) #### 1. {Topic Title} - **{final_score}分** | 热度 | 争议性 | 高价值 | 相关性 | 负向惩罚 | |------|--------|--------|--------|----------| | {trending}/4 | {controversy}/2 | {value}/3 | {relevance}/1 | -{neg_penalty} | - **推荐类型**: [短推文/Thread/评论回复] - **推荐风格**: [高价值干货/犀利观点/热点评论/故事洞察/技术解析] - **创作角度**: 建议的切入点 - **核心观点**: 可提炼的关键论点 - **相似度命中（可选）**: {max_similarity} - matched: {matched_ids} #### 2. ... ### Tier B：待定 (5-6分) - {Topic} - {final_score}分 - {原因} ### Tier C：淘汰 (<5分) - {Topic} - {final_score}分 - {原因} ## 创作建议 入选 {n} 个选题，建议优先级： 1. {最高分选题} - 理由 2. {次高分选题} - 理由 下一步：运行 `/x-create {选题}` 开始创作 ``` Append a machine-readable block for hooks/state ingestion: ```json FILTER_JSON { "schema_version": "x_skills.filter.v1", "timestamp": "{timestamp}", "profile": { "domains": ["..."], "persona_style": "..." }, "items": [ { "topic": "...", "scores": { "trending": 0, "controversy": 0, "value": 0, "relevance": 0, "neg_penalty": 0 }, "final_score": 0, "tier": "A|B|C", "reasons": ["..."], "similarity": { "max": 0.0, "matched": [{"id":"rej_xxx","score":0.0,"title":"..."}] } } ] } ``` ## Execution Steps 1. **Load materials** from x-collect or user input 2. **Read user profile** for relevance scoring and weights 3. **(Optional) SimilarityFilter** against rejected topics 4. **Score each material** on criteria and compute `FinalScore` 5. **Diversity adjustments (recommended)**: - Apply source/domain attenuation: `score *= 0.6^(N-1)` for repeated sources - Dedup per topic cluster: keep best-scoring item per cluster 6. **Categorize**: Tier A ≥7, Tier B 5-6, Tier C <5 7. **Output report** + `FILTER_JSON` 8. **(Optional) Persist feedback-loop state**: - Write Tier C items to rejected set: - `python ~/.claude/skills/x-create/scripts/x_state.py reject --topic-json '{"title":"...","reason":"...","stage":"filter"}'` - Append event: - `python ~/.claude/skills/x-create/scripts/x_state.py event --event filter.scored --payload-json '{"accepted":3,"maybe":2,"rejected":7}'` ## Example Input from x-collect: ``` 素材1: Claude 4.5 Opus发布 素材2: AI编程助手对比评测 素材3: OpenAI最新裁员新闻 ``` Scoring: ``` Claude 4.5 Opus发布: - 热度: 4/4 (刚发布，热门话题) - 争议性: 1/2 (性能vs价格讨论) - 高价值: 3/3 (新能力详解) - 相关性: 1/1 (AI/科技相关) - 总分: 9/10 ✓ 入选 AI编程助手对比评测: - 热度: 2/4 (持续话题) - 争议性: 2/2 (Cursor vs Copilot争论) - 高价值: 3/3 (实用对比) - 相关性: 1/1 (科技相关) - 总分: 8/10 ✓ 入选 OpenAI最新裁员新闻: - 热度: 3/4 (近期热点) - 争议性: 1/2 (有讨论) - 高价值: 1/3 (信息价值有限) - 相关性: 0/1 (非核心领域) - 总分: 5/10 × 待定 ``` ## Customization Users can customize weights in user-profile.md: ```yaml scoring: trending: 4 # 热度权重 controversy: 2 # 争议性权重 value: 3 # 高价值权重 relevance: 1 # 相关性权重 threshold: 7 # 入选阈值 ``` ## Integration After filtering, suggest: ``` 筛选完成！{n} 个选题入选创作池。 推荐优先创作：{top_topic}（{score}分） 下一步：运行 /x-create {top_topic} 开始创作 ```